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CIFOR-ICRAF s’attaque aux défis et aux opportunités locales tout en apportant des solutions aux problèmes mondiaux concernant les forêts, les paysages, les populations et la planète.

Nous fournissons des preuves et des solutions concrètes pour transformer l’utilisation des terres et la production alimentaire : conserver et restaurer les écosystèmes, répondre aux crises mondiales du climat, de la malnutrition, de la biodiversité et de la désertification. En bref, nous améliorons la vie des populations.

CIFOR–ICRAF publishes over 750 publications every year on agroforestry, forests and climate change, landscape restoration, rights, forest policy and much more – in multiple languages.

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Spatial modelling for predicting potential wildlife distributions and human impacts in the Dja Forest Reserve, Cameroon

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Protected areas (PAs) are currently the cornerstones for biodiversity conservation in many regions of the world. Within Africa's moist forest areas, however, numerous PAs are under significant threats from anthropogenic activities. Adequate technical and human resources are required to manage the wildlife within PAs satisfactorily. SMART (Spatial Monitoring And Reporting Tool) software has been developed to aid in fluidly displaying, managing, and reporting on ranger patrol data. These data can be analysed using spatial modelling to inform decision-making. Here we use Favourability Function modelling to generate risk maps from the data gathered on threats (fire, poaching and deforestation) and the presence of Western gorilla (Gorilla gorilla gorilla), chimpanzee (Pan troglodytes) and African forest elephant (Loxodonta cyclotis) in the Dja Forest Reserve (DFR), southern Cameroon. We show that the more favourable areas for the three study species are found within the core of the DFR, particularly for elephant. Favourable areas for fires and deforestation are mostly along the periphery of the reserve, but highly favourable areas for poaching are concentrated in the middle of the reserve, tracking the favourable areas for wildlife. Models such as the ones we use here can provide valuable insights to managers to highlight vulnerable areas within protected areas and guide actions on the ground.
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DOI:
https://doi.org/10.1016/j.biocon.2018.12.015
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